Abstract
Entity linking is a key step for automatic question and answering with knowledge graph. It has broad application prospects in Natural Language Processing, Information Retrieval and other fields. This paper constructed an entity linking model based on candidate features. Firstly, it proposed a candidate entities generation algorithm that combines knowledge base matching and word vector similarity calculation and then put forward a suitable entity disambiguation algorithm for different candidate entity generation features, so as to the linked entity is matched to the correct knowledge base entity. We did experiments on the Chinese Weibo Entity Linking data set released by NLPCC in 2013. The results showed that our model can achieve better F1 scores and recall rate than the traditional entity linking methods.
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Acknowledgements
The authors are grateful to the editors and reviewers for their helpful comments and suggestions. This research is partially supported by National Social Science Foundation project (17BXW065), National Key R&D Program of China (2018******01) and Science and Technology Research project of Henan province (172102310628).
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Li, D., Fu, Z. & Zheng, Z. An entity linking model based on candidate features. Soc. Netw. Anal. Min. 11, 50 (2021). https://doi.org/10.1007/s13278-021-00761-z
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DOI: https://doi.org/10.1007/s13278-021-00761-z